Analysis of blended learning model application using text mining method

The rapid development of networks has resulted in the recognition of blended learning as an effective learning model. The text mining method was used to analyze the blended learning practice data of 17 countries provided by the Christensen Institute. By classifying and extracting text information fr...

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Main Authors: Wang, Lin, Huang, Yanfen, Omar, Muhd Khaizer
Format: Article
Published: Kassel University Press 2021
Online Access:http://psasir.upm.edu.my/id/eprint/95790/
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author Wang, Lin
Huang, Yanfen
Omar, Muhd Khaizer
author_facet Wang, Lin
Huang, Yanfen
Omar, Muhd Khaizer
author_sort Wang, Lin
building UPM Institutional Repository
collection Online Access
description The rapid development of networks has resulted in the recognition of blended learning as an effective learning model. The text mining method was used to analyze the blended learning practice data of 17 countries provided by the Christensen Institute. By classifying and extracting text information from the use of blended learning model selection and the challenges of blended learning, the factors that hinder the implementation of blended learning were analyzed. The distribution of blended learning courses and practice models in each country were discussed, as was the influence relationship between the region and implementation model. The results demonstrate that the practice of blended learning in primary and secondary schools is mature in four courses of English, Mathematics, Science, and Social Research. The blended learning implementation model can be unaffected by the region, but more tend to “mix.” The practice cycle of blended learning becomes long and requires long-term stable support, while teachers’ ability and students’ ability preparation are the largest obstacles to the effectual development of blended learning. This study provides references for improving the efficiency of blended learning practices, especially in the aspects of practice model selection, infrastructure preparation, and teacher and student ability training.
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institution Universiti Putra Malaysia
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spelling upm-957902023-03-30T06:42:39Z http://psasir.upm.edu.my/id/eprint/95790/ Analysis of blended learning model application using text mining method Wang, Lin Huang, Yanfen Omar, Muhd Khaizer The rapid development of networks has resulted in the recognition of blended learning as an effective learning model. The text mining method was used to analyze the blended learning practice data of 17 countries provided by the Christensen Institute. By classifying and extracting text information from the use of blended learning model selection and the challenges of blended learning, the factors that hinder the implementation of blended learning were analyzed. The distribution of blended learning courses and practice models in each country were discussed, as was the influence relationship between the region and implementation model. The results demonstrate that the practice of blended learning in primary and secondary schools is mature in four courses of English, Mathematics, Science, and Social Research. The blended learning implementation model can be unaffected by the region, but more tend to “mix.” The practice cycle of blended learning becomes long and requires long-term stable support, while teachers’ ability and students’ ability preparation are the largest obstacles to the effectual development of blended learning. This study provides references for improving the efficiency of blended learning practices, especially in the aspects of practice model selection, infrastructure preparation, and teacher and student ability training. Kassel University Press 2021 Article PeerReviewed Wang, Lin and Huang, Yanfen and Omar, Muhd Khaizer (2021) Analysis of blended learning model application using text mining method. International Journal of Emerging Technologies in Learning, 16 (1). 172 - 187. ISSN 1868-8799; ESSN: 1863-0383 https://online-journals.org/index.php/i-jet/article/view/19823 10.3991/ijet.v16i01.19823
spellingShingle Wang, Lin
Huang, Yanfen
Omar, Muhd Khaizer
Analysis of blended learning model application using text mining method
title Analysis of blended learning model application using text mining method
title_full Analysis of blended learning model application using text mining method
title_fullStr Analysis of blended learning model application using text mining method
title_full_unstemmed Analysis of blended learning model application using text mining method
title_short Analysis of blended learning model application using text mining method
title_sort analysis of blended learning model application using text mining method
url http://psasir.upm.edu.my/id/eprint/95790/
http://psasir.upm.edu.my/id/eprint/95790/
http://psasir.upm.edu.my/id/eprint/95790/